Wholesale distributors of a broad range of products typically sell commodity items. As such, the margins are very small. The traditional theory is that margin degradation is caused by the competition and by customers. However, probably one of the largest causes of margin degradation is a distributor's inability to manage pricing at the customer/item level. What is typically done is that distributors will set prices for a number of specific items for a given customer, and then price everything else at a general mark up/discount. This general mark up/discount creates a cap on the amount of margin generated. In order to raise margin, the decision maker can adjust upwardly the general mark up/discount. By doing this, a large percentage of the line item pricing is changed which is very visible, and therefore, very risky. Another alternative is to manage pricing at the customer/item level. However, this management of pricing at the customer/item level often has a substantial challenge in the actual number of customer/items. A typical distributor pricing decision maker may have responsibility for one hundred customers, each purchasing one hundred to two hundred unique items. The result is tens of thousands of unique customer/item combinations. As territories grow with recent trends, the pricing management responsibility will increase, and hence, the pricing management challenge will continue to grow.
There are several packages that are known which use mechanisms in groupings of items in attempt to manage pricing. These systems typically focus on only single sales property. These prior packages are not very flexible, and they allow for potentially unfavorable price changes that may put all sales at risk. One specific prior art pricing model utilized a benchmark gross profit percent as a guideline for pricing and further included a market variance sort by item which was the difference between the existing gross profit and the projected gross profit. Other prior types of solutions include systems with too many fixed assumptions and wooden rules for price setting. There was no room or not enough room for subjective manipulation and input from a pricing decision maker or makers regarding the creation of variable benchmark statistics in the categories of sales volume, frequency (velocity) and gross profit percent and how those statistics can be utilized when manipulating customer/item level pricing.